In recent times, there has been a significant increase in attention given to research work and corresponding development activities in various industries. Typically, growth of the industry is determined by periodic launches of products and services associated with the industry. Conventionally, successful development of such products and services is initiated by influential leaders in the industry (such as researchers with well-established track records, leaders of successful companies within the industry and suchlike), who are accompanied by other emerging influential entities within the industry (such as researchers studying emerging concepts, leaders associated with emerging startups within the industry and so forth). Specifically, nurturing the emerging influential entities is crucial in deciding a progress of the industry in a subsequent time. Consequently, their presence is invaluable for the industry and identifying such emerging influential entities at a nascent stage is extremely important.
Generally, various techniques are practiced to identify the emerging influential entities. Traditionally, recommendations from well-established sources (such as successful influential leaders within the industry), surveying various entities associated with the industry (such as people working in the industry) and collecting data for the industry are some of the techniques that are used to identify the emerging influential entities within the industry. However, the aforesaid techniques are prone to being influenced by human judgment, thereby, yielding a skewed result. In addition, the techniques are laborious and time consuming. Moreover, such techniques are reliant on analysis within constant time duration, overlooking a change achieved by emerging influential entities in a time period outside the time duration of consideration. Additionally, the traditional techniques are not dynamic, such that they cannot be adapted to different user requirements, thus, generating limited results.
Moreover, a deciding factor of potential of the emerging influential entities may be associated with how they are associated to multiple other influential entities. However, manually tracking such associations between various emerging influential entities may not be feasible. For example, the associations may change with time and it may not be possible to regularly update such information for a large number of the emerging influential entities. Therefore, maintaining records of influential entities within different industries by using conventional techniques is generally inefficient, cumbersome, unreliable, and does not allow identification of the emerging influential entities.
Therefore, in light of the foregoing discussion, there exists a need to overcome the aforementioned drawbacks associated with the conventional techniques of identifying emerging influential entities within various industries.